JP5641281B2 - Multivariate analysis of inflammatory response mediator-related genetic polymorphisms for predicting outcomes in critically ill patients - Google Patents

Description

  The present invention relates to pro-inflammatory mediators as predictors to provide more accurate outcome predictions in sick or critically ill patients, such as those housed in ICU or other parts of the hospital Relates to the use of one or more genetic polymorphisms.

  In the field of emergency intensive care medicine, a great variety of studies have been conducted on the pathophysiology of severe conditions such as sepsis, traumatic injury, and burns. In particular, the involvement of innate immunity in the pathophysiology of sepsis has been extensively studied, and new findings have been made to clarify the pathophysiology of sepsis (Non-patent Document 1). These findings have proved that recognition of pathogens by the innate immune system and subsequent production of pro-inflammatory mediators such as cytokines play an important role in the pathophysiology of sepsis (Non-patent Document 2). These findings have also demonstrated that there are individual differences in pathogen recognition and cytokine production, which may be related to differences in genetic background (Non-Patent Document 3). In fact, several genetic association studies have reported that certain genetic polymorphisms are associated with clinical symptoms or response to certain types of treatment in critically ill patients (Non-Patent Documents 4-6) The possibility of personalized medicine or tailor-made medicine based on genetic polymorphism has been suggested (Non-patent Document 7). On the other hand, a study of the association between specific genetic polymorphisms in critically ill patients and outcome, disease severity, and / or duration of mechanical ventilation is an attempt to identify genetic risk factors or outcome predictors Although it is implemented as a part, no final conclusion has been obtained (Non-patent Documents 8-10).

The present inventors have previously reported the association between genetic polymorphism and disease severity and clinical outcome in patients with sepsis (Non-patent Documents 11 and 12). Genetic polymorphism and clinical outcome and Sequential Organ Failure Assessment (SOFA) score of 5 in patients with inflammatory response syndrome
Or the correlation between being more than (> = 5) was proved (nonpatent literatures 12 and 13). The possibility that genetic polymorphisms associated with outcomes in critically ill patients can be used in combination with traditional clinical parameters such as disease severity and systemic symptoms to better predict outcomes in ICU patients Has not been investigated.

  APACHE (APACHE, The Acute Physiology and Chronic Health Evaluation) II score (Non-Patent Documents 12 and 14) is an index typically used for measuring the severity of disease in ICU patients. This score score is calculated for each ICU patient as the sum of physiological variables, age and chronic health points, and is used not only to assess disease severity but also as a prognostic predictor. Physiological variables directly reflect disease severity, and age and chronic disease score are background factors that contribute to disease severity. In addition to the APACHE II score, factors such as sex, past treatment history, and infection have been reported to affect the prognosis of ICU patients (Non-patent Documents 15-18).

  In many clinical conditions such as sepsis, pancreatitis, traumatic injury, and shock, organ failure in ICU patients due to exacerbated inflammation is a critical factor in determining the clinical course and outcome of individual patients (Non-patent document 19). The severity of disease in ICU patients increases with the number of damaged organs, and assistance with various artificial organs is utilized depending on the number and type of damaged organs. An association between specific genetic polymorphisms and organ failure in critically ill patients has often been reported (Non-patent Documents 20-22). Among the various types of organ failure observed in critically ill patients, acute lung injury has been investigated most closely to elucidate the relationship between this clinical manifestation and genetic polymorphisms of pro-inflammatory cytokines (Non Patent Literature 23-25).

  Genetic polymorphisms in ICU patients may affect not only their survival but also the number of damaged organs and the need for mechanical ventilation during ICU stay, and the clinical course and outcomes of ICU patients have a long association with them Not only traditional demographic and / or clinical factors known (eg APACHE II score, infection, age, gender, past treatment history), but also genetic factors (eg inflammation) associated with the same outcome criteria The possibility of depending on the genetic polymorphism involved in the production of facilitating mediators has not been revealed previously.

  The following references and all publications mentioned in this specification are incorporated by reference in their entirety.

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A feature of the present invention is that the determination or prediction of the clinical outcome of a seriously ill patient is performed by collecting genomic DNA from the patient and detecting one or more genetic polymorphisms in the genomic DNA of the patient That is. The genetic polymorphism can be a polymorphism associated with the production of pro-inflammatory mediators. The genetic polymorphism can include an allele where position -308 of the TNF-α gene is G or A. The genetic polymorphism can include an allele where position -31 of the IL-1β gene is C or T. The genetic polymorphism can include the RN1 allele with respect to a variable number of tandem repeats (VNTR) in intron 2 of the IL-1ra gene.

Methods are provided for determining or predicting clinical outcome (or likelihood of outcome) for a sick or seriously ill patient, such as a patient admitted to an intensive care unit (ICU). The method can include collecting genomic DNA from the patient to detect one or more genetic polymorphisms in the patient's genomic DNA. The genetic polymorphism can be a polymorphism associated with the production of pro-inflammatory mediators. The genetic polymorphism can include an allele where position -308 of the TNF-α gene is G or A. The genetic polymorphism can include an allele where position -31 of the IL-1β gene is C or T. The genetic polymorphism can include the RN1 allele with respect to a variable number of tandem repeats (VNTR) in intron 2 of the IL-1ra gene. Determining the clinical outcome for the patient can include determining clinical factors. The clinical factor can be an APACHE II score, infection, age, gender, and / or past treatment history. Detecting genetic polymorphism in a patient's genomic DNA can be accomplished by using an automated sequence detection system. Detection of genetic polymorphism in the patient's genomic DNA can be accomplished by electrophoresis. Detecting the genetic polymorphism can include amplifying a gene containing the polymorphism with an automatic PCR thermal sequencer. The patient can have clinical symptoms that require intensive treatment. The clinical symptoms can be sepsis, traumatic injury, severe acute pancreatitis, fulminant hepatitis, or those in recovery phase after surgery.

A method for determining or predicting a clinical outcome (or likelihood of outcome) for a sick or seriously ill patient, such as a patient admitted to an intensive care unit (ICU), is to collect DNA from the patient, the patient's genome Detecting a genetic polymorphism in the DNA, and if the genetic polymorphism is detected and when clinical factors are measured, the clinical outcome for the patient is death, organ failure, and / or lung injury Determining. The clinical factor can be an APACHE II score, infection, age, gender, and / or past treatment history. The clinical outcome can be ICU death, organ failure, and / or lung injury. The genetic polymorphism can include an allele where position -308 of the TNF-α gene is G or A, the clinical factor can be an APACHE II score, and the clinical outcome is an ICU Can be death. The genetic polymorphism can include an allele where position 31 of the IL-1β gene is C or T, the clinical factor can be an APACHE II score, and the clinical outcome is Can be death. The genetic polymorphism can include an allele in which the TNF-α gene at position -308 is G or A, and the IL-1β gene at position -31 is C or T, and the clinical factor Can be an APACHE II score and the clinical outcome can be death in ICU. The genetic polymorphism can include an RN1 allele with respect to a VNTR in intron 2 of the IL-1ra gene, the clinical outcome can be lung injury, and the clinical factor is an APACHEII score, past treatment history And / or infection. Past treatment history can be heart disease.

  The present teachings will be described with reference to the accompanying drawings. The drawings are intended to be illustrative and not limiting of the present teachings.

FIG. 5 shows ROC curves for predicting mortality (eg, death in ICU) in all patient groups. Four different combinations of clinical and genetic parameters were used for the prediction. Curve 1: Infection + APACHE II score (ROC-AUC = 0.77); Curve 2: Infection + APACHE II score + TNF-α-308 (ROC-AUC = 0.78); Curve 3: Infection + APACHE II score + IL-1β -31 (ROC-AUC = 0.80); and curve 4: infection + APACHE II score + TNF-α-308 + IL-1β-31 (ROC-AUC = 0.81).

It is a figure which shows the ROC curve for the prediction of the death by ICU in a sepsis subgroup. Four different combinations of clinical and genetic parameters were used for the prediction. Curve 1: APACHE II score alone (ROC-AUC = 0.68); Curve 2: APACHE II score + TNF-α-308 (ROC-AUC = 0.72); Curve 3: APACHE II score + IL-1β-31 (ROC- AUC = 0.77); and Curve 4: APACHE II score + TNF-α-308 + IL-1β-31 (ROC-AUC = 0.80).

  The present invention and method can be used to predict the outcome of a sick or seriously ill patient to support a healthcare business. As an example, the present invention can be used in hospital tissues such as intensive care units and trauma treatment units to determine the clinical course or outcome of critically ill patients. Locations where the present invention can be used are not limited and may include nursing homes, hospitals, field hospitals, and the like. The present invention can facilitate the assessment of the severity of a patient's condition. By providing a better understanding of the severity of a patient's condition, the present invention assists caregivers, health care providers, or patient relatives in medical decisions such as treatment decisions and end-of-life decisions be able to.

  Although the present invention will be described with respect to an ICU, this is exemplary only and the present invention applies to patients in any location. Genetic polymorphisms associated with pro-inflammatory mediators can be significantly associated with the outcome of sick or seriously ill patients. Thus, genetic polymorphism can be used as a predictor of outcome in patients with illness or serious illness. The genetic polymorphism can be used alone or in combination with other genetic polymorphisms and / or clinical factors conventionally used to predict patient outcome. For example, the inventors have determined that a ICU patient's mortality risk or ICU mortality rate is one or more genetic factors and / or one or more genetic factors after the patient is admitted to, for example, an ICU. We found that it can be determined based on the combination with clinical factors. One or more genetic factors, such as genetic polymorphism, allows for an accurate prediction of the clinical course and outcome of the ICU patient. The genetic polymorphism may be involved in the production of pro-inflammatory mediators such as cytokines. Additionally or alternatively, the genetic polymorphism can be used to evaluate or further confirm the patient outcome predicted by conventional clinical factors.

  A patient's genomic DNA can be collected and the clinical outcome of the patient can be determined based on the presence of a genetic polymorphism.

Genetic polymorphisms associated with one or more pro-inflammatory mediators are single nucleotide polymorphisms (SNPs) such as tumor necrosis factor-α (TNF-α) -308G / A, TNF-α-238G / A , LTα-T / C, Interleukin-1β (IL-1β) -511A / G, IL-1β-31C / T, IL-6-174G / C, IL-6-634G / C, IL-10-1082A / G, IL-10-819C / T, IL-10-592C / A, macrophage migration inhibitory factor (MIF) -173G / C, CD14-159G / A, protein C (PROC) -1654C / T, PROC-1641G / A and / or PROC-1476A / T. The genetic polymorphism can include the presence of a G or A allele at position -308 . The genetic polymorphism can include the presence of a C or T allele at position -31 of the IL-1β gene. The genetic polymorphism can include the presence of the RN1 allele with respect to a variable number of tandem repeats (VNTR) within intron 2 of the IL-1ra gene. The patient's clinical outcome can include patient mortality or ICU mortality, patient organ failure, and / or patient lung failure. The patient can be in a clinical condition that requires intensive care. The clinical condition can be sepsis, traumatic injury, severe acute pancreatitis, fulminant hepatitis, and / or postoperative recovery.

  Other genetic polymorphisms can also be used separately or in combination with one or more clinical factors that determine patient outcome.

A patient's clinical outcome can be determined based on one or more genetic factors and / or a combination of one or more genetic factors and clinical factors. The one or more genetic factors can be one or more genetic polymorphisms associated with the production of pro-inflammatory mediators. The genetic polymorphism is, for example, the presence of a G or A allele at position -308 , the presence of a C or T allele at position -31 of the IL-1β gene, and / or intron 2 of the IL-1ra gene The presence of the RN1 allele with respect to a variable number of tandem repeats (VNTR). The clinical factor can be a high APACHE II score, infection, age, sex, and / or past disease. Past disease or past treatment history can include various diseases such as heart disease, respiratory disease, liver disease, diabetes, malignancy, kidney disease, and / or brain disease.

For example, the clinical outcome of ICU mortality is that the detected genetic polymorphism is the presence of G or A at position -308 of the TNF-α gene and / or the C or T allele at position -31 of the IL-1β gene It can be determined if it includes the presence of a gene. The clinical outcome of death is associated with an ICU score range of about 50-71, such as 55-71, 65-71, or 70-71 (APACHE II score referring to ICU patients). The clinical outcome of ICU mortality is when the APACHE II score is in the range of approximately 65-71, and when the detected genetic polymorphism is the presence of G or A at position -308 of the TNF-α gene and / or Alternatively, it can be determined if it includes the presence of a C or T allele at position -31 of the IL-1β gene.

  The clinical outcome of lung failure can be determined when the detected genetic polymorphism includes the presence of the RN1 allele for VNTR in intron 2 of the IL-1ra gene. Clinical outcome of lung failure is when the detected genetic polymorphism includes the presence of the RN1 allele for VNTR in intron 2 of the IL-1ra gene, and the following clinical factors: APACHE II range 50-71, It can be determined if there is at least one of heart disease and / or infection.

  A patient's clinical outcome can be determined based on one or more genetic factors and / or a combination of one or more genetic factors and clinical factors. The inventors have found that the clinical factors conventionally used to predict patient outcomes can be used in combination with genetic factors to determine the patient's clinical outcomes more accurately than using only the clinical factors. . In other words, if a patient has one or more specific genetic polymorphisms associated with clinical outcomes and falls within the range of traditional clinical factors associated with clinical outcomes, the likelihood of the occurrence of specific clinical outcomes Is significantly greater than when considering only clinical factors or parameters. Here, the term “significantly” means that the predicted outcome is at least 50%, such as 50% -100%, 60% -90%, or 70% -80%, than when the invention is not used. Means accurate. For example, two clinical factors (APACHE II score and infection) and one genetic factor (TNF-α-308) were able to perform more accurate mortality predictions, and two clinical factors (APACHE II score) And infection) and two genetic factors (TNF-α-308 and IL-1β-31) found that more accurate mortality prediction could be performed.

  A method for determining clinical outcome for a patient, eg, a patient admitted to an ICU, is to collect genomic DNA from the patient and one or more associated genes associated with pro-inflammatory mediators in the genomic DNA Detecting the presence of a genetic polymorphism. Collection of genomic DNA from the patient can be performed by any method known in the art. Genomic DNA can be collected from any biological sample from the patient. The biological sample can be blood, serum, urine, prostate fluid, seminal plasma, semen, tissue extract sample, or biopsy sample. Biological samples can include, for example, collecting blood from a patient and extracting genomic DNA from EDTA anticoagulated whole blood. Amplification of related genes from genomic DNA can be performed using an automated polymerase chain reaction (PCR) thermal sequencer or using any other suitable method known in the art. Detection of genetic polymorphisms associated with pro-inflammatory cytokines can be performed using any detection system known in the art. An automated sequence detection system such as the ABI PRISM 7000 Sequence Detection System (AppliedBiosystems, Foster City, CA) can be used before and after PCR to detect each SNP, for example. A DNA fragment containing a variable number of repeat units within intron 2 of the IL-1ra gene can be amplified and obtained by PCR in a Bio-Rad iCycler (Bio-Rad Laboratories, Hercules, CA). The resulting PCR product can be analyzed by electrophoresis in an Agilent Technologies Bioanalyzer 2100 (Agilent Technologies Bioanalyzer 2100, Agilent Technologies, Santa Clara, Calif.).

  Two genetic polymorphisms, TNF-α-308GA and IL-1β-31CT / TT tend to have a significant correlation with ICU mortality in critically ill patients, especially those with sepsis. The use of genotypes at these two polymorphic loci in combination with or without traditional clinical predictors can allow for a more accurate prediction of outcome in ICU patients. The clinical predictor can be a high APACHEII score, gender, past treatment history, and / or infection. Use of the genetic polymorphism, TNF-α-308GA and IL-1β-31CT / TT in combination with the APACHE II score tends to have a significant correlation with ICU mortality in critically ill patients.

  The teachings of the present application can be more fully understood by reference to the following examples and the data obtained.

Materials and Methods Study Subjects: Subjects in this study were sepsis, traumatic injury, severe acute pancreatitis, fulminant hepatitis, housed in ICU of Chiba University Hospital between October 2001 and November 2007. And 224 patients in clinical condition requiring intensive care, such as postoperative recovery (patient group), and 294 healthy volunteers (control group).

  Diagnosis of sepsis was performed according to the criteria described in the agreement document by the American College of Chest Physicians / Society of the Critical Care Medicine Consensus Conference (Non-patent Document 26) ). This research was approved by the Chiba University Graduate School of Medical Researcher Ethics Review Board. Informed consent was obtained from participants in each study or their families.

  Data collection: Age, gender, and past treatment history (heart disease, respiratory disease, liver disease, kidney disease, malignancy, diabetes, autoimmune disease, and brain disease) are recorded for each patient at ICU admission, APACHE II score was calculated within 24 hours of accommodation.

Clinical status recorded as past treatment history: Clinical status recorded as "Past treatment history" included the following states.
1) Heart disease: Hypertension, angina pectoris, ischemic heart disease during medication, or New York Heart Association class III / IV.
2) Respiratory disease: severe motor restriction, ie chronic restrictive, obstructive or defective disease leading to inability to climb stairs or perform housework; or reported chronic hypoxemia, hypercapnia, 2 Secondary polycythemia, pulmonary hypertension (> 40mmHg), or ventilator dependent.
3) Liver disease: History of child classification B / C, biopsy-diagnosed cirrhosis, portal hypertension, or liver failure / hepatic coma.
4) Diabetes: Diabetes mellitus diagnosed and treated at medical institutions.
5) Malignant tumors: All types of malignant tumors other than leukemia and lymphoma.
6) Kidney disease: Chronic kidney disease classified as Stage III or higher of K / DOQI (Kidney Disease Outcome Quality Initiative, Non-Patent Document 27).
7) Brain disease: Cerebral infarction, intracranial hemorrhage.
Autoimmune diseases treated with immunosuppressants or high-concentration steroids were excluded from the “Past Treatment History”. Malignant tumor diseases treated with chemotherapy or radiation therapy were also excluded.

  Definition of outcome: Mortality and organ failure and lung injury during ICU residence were considered outcome criteria to be predicted in this study. The SOFA score calculated during the ICU residence period was used as an indicator of the severity of organ failure. SOFA scores were calculated at the time of ICU admission and daily from 6: 00-6: 30. The maximum SOFA score during the ICU period was indicated as SOFA max, and a SOFA max of 10 or more was judged to indicate the presence of severe organ failure. The use of mechanical ventilation was considered an indicator of lung injury. If the mechanical ventilation period exceeded 7 days, it was judged to indicate the presence of severe lung injury.

  Sample collection and DNA extraction: Blood samples were collected from subject patients at the time of ICU admission and once daily thereafter via an arterial catheter. All daily blood samples were collected between 6: 00-6: 30 am. Venous blood samples were collected from healthy volunteers via the anterior cubital vein. Blood samples were collected in blood collection tubes to which ethylenediaminetetraacetic acid (EDTA) was added as an anticoagulant. Genomic DNA was extracted from EDTA-anticoagulated whole blood using QIAGEN QIAamp DNA Mini Kit (QIAGEN, Valencia, CA) according to the manufacturer's instructions.

  Genetic polymorphism analysis: Sixteen different genetic polymorphisms associated with cytokine production were examined in this study. They are single nucleotide polymorphisms (SNPs) at 15 different loci, all of which are located in the promoter region of the related gene, and variable tandem repeats (VNTR) in intron 2 of the IL-1ra gene It is. The following SNP loci were examined: tumor necrosis factor-α (TNF-α) -308G / A, TNF-α-238G / A, LTα-T / C, interleukin-1β (IL-1β)- 511A / G, IL-1β-31C / T, IL-6-174G / C, IL-6-634G / C, IL-10-1082A / G, IL-10-819C / T, IL-10-592C / A, macrophage migration inhibitory factor (MIF) -173G / C, CD14-159G / A, protein C (PROC) -1654C / T, PROC-1641G / A, and / or PROC-1476A / T.

Real-time polymerase chain reaction (PCR) assays were performed for genotyping of 15 SNP loci using specific fluorescently labeled probes. PCR primers and fluorogenic probes were designed for each SNP and analyzed using PrimerExpress ^™ version 1.5 software (Applied Biosystems, Foster City, CA). The fluorescence of each well was measured using ABI PRISM 7000 Sequence Detection System (Applied Biosystems, Foster City, Calif.) Before and after PCR. Detailed methods of SNP genotyping have been published previously (Non-patent Document 12).

  The polymorphic region within intron 2 of the IL-1ra gene contains a variable number of 86 bp tandem repeat units. A DNA fragment containing this region was amplified by PCR in a Bio-Rad iCycler (Bio-Rad Laboratories, Hercules, Calif.) And the resulting PCR product was electrophoresed in an Agilent Technologies Bioanalyzer 2100 (Agilent Technologies, SantaClara, Calif.). Analyzed by electrophoresis. Alleles with four, two, five, three, and six 86 bp tandem repeat units (labeled RN1, RN2, RN3, RN4, and RN5, respectively) are 410 bp, 240 bp, and 500 bp, respectively. Amplification products of 325 bp and 595 bp are produced under the experimental conditions employed. Detailed methods of VNTR genotyping have been published previously (Non-patent Document 28).

Blood IL-6 levels: Blood IL-6 levels in ICU patients were analyzed once daily during and during ICU admission. Analysis, Rapid chemiluminescent enzyme immunoassay (CLEIA), Fujirebio-human IL-6 CLEIA cartridge (Fujirebio, Tokyo, Japan) automated CLEIA system Fujirebio Lumipulse F ^® with a (Fujirebio Lumipulse f ^R, Fujirebio , Tokyo, Japan) (Non-patent Documents 12 and 29). Plasma was immediately separated from blood samples collected as described in the section “Sample collection and DNA extraction” and stored frozen (−70 ° C.) until analysis (Non-patent Document 12). The maximum blood IL-6 level during the ICU period is indicated as IL-6 Max.

Statistical analysis: whether the genotype frequencies is consistent with the Hardy-Weinberg equilibrium (Hardy-Weinberg equilibrium), for the control subjects and patients, were tested using the χ ² goodness-of-fit test (χ ² goodness of fit test) . Differences between patient group and control group regarding genotype frequency and allele frequency at each polymorphic locus were examined by chi ² test. Effects of APACHE II score, age, gender, past treatment history, infection, and genetic polymorphism on ICU mortality, SOFA Max (> 10), mechanical ventilation, and mechanical ventilation in all patient groups (n = 224) Periods (> 7 days) were examined by applying backward selection with a p-value of 0.05 by a stepwise multivariable logistic regression analysis applying. The interaction between infection and other predictors was examined for each response variable. A similar analysis was performed for the sepsis subgroup (n = 123). The predictive power of each model is expressed as a receiver-operating characteristics (ROC) curve and a corresponding area under the curve derived by leave-one-outcross-validation. curve (AUC)). All p values were two-sided. A p value of less than 0.05 was considered statistically significant.
All statistical analyzes were performed using SAS ver9.1.3 for Windows (SAS Institute, Inc., Cary, NC) and Rver. 2.6.1 for Windows (R Development Core Team) (Non-patent Document 30).

Results Impact of 16 different genetic polymorphisms associated with pro-inflammatory mediators and conventional demographic and / or clinical parameters (APACHEII score, age, gender, past treatment history, and infection) on ICU mortality In addition to studying disease severity (SOFA), mechanical ventilation, and mechanical ventilation duration during ICU residence, the study was performed by multivariate logistic regression analysis in all patient groups (n = 224). This revealed a factor that significantly correlated with the outcome of ICU patients. Subgroup analysis was performed in a similar manner in the sepsis subgroup (n = 123). TNF-α-308GA (odds ratio, 8.01; 95% CI, 1.30-49.92; p = 0.025), IL-1β-31CT (odds ratio, 3.25; 95% CI, 1.21-8.72; p = 0.020), and APACHE The II score (odds ratio, 1.08; 95% CI, 1.02-1.13; p = 0.004) correlated significantly with ICU mortality in all patient groups. As detailed below, factors significantly correlated with ICU mortality in the septic subgroup were TNF-α-308GA (odds ratio, 12.92; 95% CI, 1.25-144.79; p = 0.038), IL-1β -31 CT / TT (odds ratio, 9.04; 95% CI, 1.12-72.75; p = 0.039), and APACHE II score (odds ratio, 1.06; 95% CI, 1.01-1.12; p = 0.030). This finding for the sepsis subgroup was thus similar to that for the entire patient group. ROC analysis compares two clinical parameters and two genetic parameters (TNF-α-308 and IL-1β-31) compared to a combination of clinical parameters only (APACHE II score and infection) (ROC-AUC = 0.77) Has been shown to allow a more accurate prediction of ICU mortality in all patient groups (ROC-AUC = 0.81). Similarly, by using two genetic parameters and the APACHE II score (ROC-AUC = 0.80), ICU death in the septic subgroup compared to using the APACHE II score alone (ROC-AUC = 0.68) The rate could be predicted more accurately.

  The 224 ICU patients studied included 123 septic patients, 47 patients undergoing elective surgery (cardiac surgery, 25; abdominal surgery, 9; nervous / spine surgery, 6; 4 cases), 15 severe acute pancreatitis, 9 traumatic injury patients, 6 cardiopulmonary arrest patients, 5 autoimmune disease patients, 4 respiratory diseases, 4 hemorrhagic shock patients, 4 Examples include acute renal failure patients, 3 acute drug addiction patients, 2 acute myocardial infarction patients, 1 burn patient, and 1 acute abdomen patient. Table 1 summarizes the background characteristics of all patient groups and septic subgroups.

  Prior to detailed analysis of genetic polymorphisms in the ICU patient group, we confirmed that the genotype frequency was consistent with the Hardy-Weinberg equilibrium for all 15 SNP loci examined in the control group in this study. Furthermore, for any of the 16 genetic polymorphisms analyzed, there was no significant difference in genotype frequency between the patient group and the control group.

  Table 2 summarizes the results of SNP genotyping in the patient group. Of the 15 SNP loci analyzed, IL-6-174 was found to be monomorphic (Table 2). Three different genotypes were identified for VNTR in intron 2 of the IL-1ra gene: RN1 / 1 in 197 patients, RN1 / 2 in 21 patients, and RN1 / 3 in 6 patients . Based on these findings, IL-6-174 was excluded from the 16 genetic polymorphisms tested and 15 different polymorphisms were examined for correlation with clinical course and outcome in ICU patients.

  Multivariate analysis revealed that three factors were significantly correlated with ICU mortality in all patient groups. They are TNF-α-308GA (odds ratio, 8.01; 95% CI, 1.30-49.92; p = 0.025), IL-1β-31CT (odds ratio, 3.25; 95% CI, 1.21-8.72; p = 0.020) , And APACHE II score (odds ratio, 1.08; 95% CI, 1.02-1.13; p = 0.004). Infection was found to correlate with ICU mortality, but the correlation was not statistically significant (odds ratio, 3.22; 95% CI, 0.98-10.54; p = 0.053). Factors significantly correlated with ICU mortality in the sepsis subgroup were TNF-α-308GA (odds ratio, 12.92; 95% CI, 1.25-144.79; p = 0.038), IL-1β-31CT / TT (odds ratio, 9.04 95% CI, 1.12-72.75; p = 0.039), and APACHE II score (odds ratio, 1.06; 95% CI, 1.01-1.12; p = 0.030). This indicates that the findings in the sepsis subgroup are similar to those in all patient groups (Table 3).

  APACHEII score (odds ratio, 1.19; 95% CI, 1.12-1.25; p <0.001) and infection (odds ratio, 4.98; 95% CI, 2.47-10.05; p <0.001) during ICU retention in all patient groups It was significantly correlated with a SOFA max value of 10 or more (> 10). In the septic subgroup, APACHE II scores (odds ratio, 1.16; 95% CI, 1.09-1.25; p <0.001) and female gender (odds ratio, 0.36; 95% CI, 0.14-0.91; p = 0.03 ) Significantly correlated with this outcome measure.

  Four parameters were significantly correlated with the efficiency of mechanical ventilation in all patient groups. They are IL-1ra VNTR RN1 / 1 (odds ratio, 2.69; 95% CI, 1.01-7.18; p = 0.048), history of heart disease (odds ratio, 3.28; 95% CI, 1.14–7.64; p = 0.006) , APACHE II score (odds ratio, 1.15; 95% CI, 1.10-1.22; p <0.001), and infection (odds ratio, 2.16; 95% CI, 1.09-4.38; p = 0.028). In the sepsis subgroup, only the APACHE II score (odds ratio, 1.06; 95% CI, 1.01-1.12; p = 0.030) was significantly correlated with this outcome criterion (Table 4).

  APACHEII score (odds ratio, 1.11; 95% CI, 1.06-1.16; p <0.001) and infection (odds ratio, 9.28; 95% CI, 4.24-20.25; p <0.001) machine over 7 days in all patient groups Significantly correlated with ventilation period. In the sepsis subgroup, only the APACHE II score (odds ratio, 1.08; 95% CI, 1.03-1.14; p = 0.002) was significantly correlated with this outcome criterion (Table 5).

  The predictive ability of various combinations of the four ICU mortality predictors identified by multivariate analysis was evaluated by ROC analysis. Compared to a combination of clinical parameters only (APACHE II score and infection) (ROC-AUC = 0.77), a combination of two clinical parameters plus one genetic parameter more accurately predicts ICU mortality in all patient groups (TNF-α-308, ROC-AUC = 0.78; IL-1β-31, ROC-AUC = 0.80). The use of a combination of two clinical parameters and two genetic parameters enabled even more accurate predictions (ROC-AUC = 0.81) (Figure 1). These results were also obtained in the sepsis subgroup. Compared to the APACHE II score alone (ROC-AUC = 0.68), when combined with one genetic parameter in addition to the APACHE II score (TNF-α-308, ROC-AUC = 0.72; IL-1β-31, ROC- (AUC = 0.77) ICU mortality could be predicted more accurately. The use of a combination of two clinical parameters and two genetic parameters enabled even more accurate predictions (ROC-AUC = 0.80) (Figure 2).

  Consistent with the results described in this example, TNF-α-308, IL-1β-31, and APACHE II scores independently correlated with ICU mortality in both all patient groups and septic subgroups. The odds ratio for the APACHE II score did not vary significantly between the total patient group (1.08) and the septic subgroup (1.06), but the odds ratio for TNF-α-308 GA in the septic subgroup (12.92) Higher than the one (8.01). Furthermore, the odds ratio (9.04) for IL-1β-31CT / TT in the sepsis subgroup was higher than the odds ratio (3.25) for IL-1β-31CT in all patients. These results suggest that the impact of genetic polymorphism on ICU mortality is greater in the sepsis subgroup than in the total patient group.

  The central role of cytokines in the pathology of critically ill patients is now well recognized. Hypercytokinemia is currently regarded as an indicator of the severity of severe illness, and the progression of hypercytokinemia is itself known to play a role in the worsening of clinical conditions (non-patented References 15, 31). In this study, the pro-inflammatory cytokine index IL-6 Max during ICU admission was significantly higher in the sepsis subgroup (Table 2, p <0.001), indicating that all patients with hypercytokinemia in the sepsis subgroup Suggests heavier than the group. Consistent with this conclusion, the APACHE II score and SOFA Max in the septic subgroup tended to be higher than those in all patient groups. This indicates that the clinical status is more severe in the sepsis subgroup than in the entire patient group. Previous results suggested that some genetic polymorphism was associated with IL-6 overproduction and closely correlated with the clinical outcome of critically ill patients (12, 13). This allows two other genetic polymorphisms associated with the pro-inflammatory cytokines examined in this study, TNF-α-308 and IL-1β-31, to have heavier hypercytokinemia and heavier clinical status. It can be explained that the outcome prediction in the septic group shown has a great influence.

  TNF-α is the most widely studied cytokine in genetic polymorphism studies in septic patients. TNF-α-308G / A is a SNP within the promoter amount region of the TNF-α gene and is a typical functional genetic polymorphism of TNF-α. A allele at this SNP locus is associated with increased transcription of the TNF-α gene in human B cells (Non-patent Document 32) and circulating singles in humans stimulated with bacterial lipopolysaccharide (LPS). It has been reported to be associated with high production of TNF-α by nuclear leukocytes and granulocytes (Non-patent Document 33), while in 87 healthy male volunteers who received LPS injections induced experimental endotoxemia No significant correlation was observed between this SNP and TNF-α production (Non-patent Document 34). The correlation of TNF-α-308G / A with sepsis, severe sepsis, and septic shock is still unclear. Stuber et al. Reported that no significant correlation was detected between this SNP and the incidence of severe sepsis in 80 patients who developed severe sepsis during postoperative recovery. (Non-patent Document 35). On the other hand, Dianliang et al have shown a correlation between this SNP and the incidence of septic shock in 208 patients with severe acute pancreatitis (Non-patent Document 36). Menges et al. Reported that this SNP was associated with sepsis incidence and mortality in 159 patients with severe traumatic injury (37).

  In addition, the frequency distribution of IL-1β-31 and IL-1β-511 genotypes (CC, CT, and TT) was 98.2% in the patient group (Table 2) and the control group (data not shown), respectively. And was about the same as shown by being 97.7%. Similar results reported by El-Omaret al. Suggest that the inheritance patterns of genotypes at these two polymorphic loci are similar within a population of established ethnic groups ( Non-patent document 38). Nevertheless, in this example, IL-1β-31 alone was significantly correlated with ICU mortality in both the whole patient group and the septic subgroup, leading to the clinical outcome of these two polymorphic severe patients This suggests that there may be a slight difference in the impact of. Findings inconsistent with the results of this example have been obtained regarding the correlation of IL-1β-31 and IL-1β-511 with sepsis. That is, Barber et al. Reported no significant correlation between the polymorphism in IL-1β-31 and the risk of developing severe sepsis and mortality in 228 patients with severe burns. (Non-Patent Document 39) and Ma et al. Suggest that IL-1β-511 may be a risk factor for high sepsis severity in 60 ICU patients diagnosed with sepsis (Non-patent document 28). It should be noted that neither of the above two studies simultaneously examined these two genetic polymorphisms in the promoter region of the IL-1β gene as in this example. .

  APACHEII score and infection were factors that correlated with SOFA Max (> 10) during ICU admission in all patient groups, whereas APACHE II score and female sex correlated with this outcome measure in the sepsis subgroup. There was no significant correlation between genetic polymorphism and SOFA Max during ICU admission, an indicator of worsening clinical status, in either the entire patient group or the septic subgroup. In contrast to the results in the septic subgroup (all ages 50 years and older), recent findings supporting gender affect the outcome of critically ill patients suggest a feminine advantage (40) -42). Frink et al. Demonstrated that women (not over 50 years) are less susceptible to hypercytokinemia and multiple organ failure than men of the same age among patients with various traumatic injuries (Non-patent document 40). Adrie et al. Found that, among patients with severe sepsis, hospital-wide mortality was significantly lower in females (over 50 years) than males of the same age, and between younger men and women in the younger group Reported that there was no significant difference (Non-patent Document 41). Choudhry et al. Scrutinized the difference in the effects of male and female hormones on post-traumatic immune responses and reversed the androgen's inhibitory effect in maintaining immune function following injury. Emphasized the role of estrogen (Non-patent Document 42). These findings, together with our findings, almost demonstrating the superiority of femininity in terms of survival and good recovery from traumatic disorders.

  Extensive studies have been reported to identify genes associated with acute lung injury / acute respiratory distress syndrome and ventilator-associated lung injury, with many SNPs listed as candidates for disease-modifying loci (Non-patent Document 43). The results of the present example show that IL-1ra VNTR RN1 / 1 is the only genetic marker that significantly correlates with mechanical ventilation in all patient groups, and any of the genetic polymorphisms examined is the outcome criterion in the sepsis subgroup And not significantly correlated. Furthermore, there were no genetic polymorphisms that were significantly correlated with mechanical ventilation duration in either the total patient group or the sepsis subgroup. The RN2 allele of IL-1ra VNTR was significantly correlated with mortality in septic patients, but not the RN1 allele (Non-patent Document 28). Furthermore, IL-1ra VNTR itself, Lam and dos Santos (Non-patent Document 43), is not included in the list of candidate disease-modifying genes.

  Four promising predictors of ICU mortality, two clinical parameters and two genetic parameters, were identified by multivariate analysis and used in various combinations to predict mortality in all patient groups and septic subgroups . ROC analysis adds one or two genetic parameters (TNF-α-308GA and / or IL-1β-31CT) to two clinical parameters compared to a combination of clinical parameters only (APACHE II score and infection) And ICU mortality in all patient groups could be predicted more accurately. Consistent with this, adding one or two genetic parameters to the APACHE II score could more accurately predict ICU mortality in the sepsis subgroup than the APACHE II score alone. However, the concomitant improvement in predictive ability was greater in the sepsis subgroup, as indicated by changes in ROC-AUC (0.77 to 0.81 in all patients groups, 0.68 to 0.80 in the sepsis subgroup). This is due to the use of genetic parameters (genotypes of related polymorphic loci) (TNF-α-308GA and IL-1β-31CT / TT) in combination with clinical predictors such as the traditional APACHE II score. This suggests that more accurate prediction of the outcome of ICU patients who have developed the disease is possible.

  In summary, the relationship between genetic polymorphisms in critically ill patients and ICU mortality, disease severity, mechanical ventilation performance, and mechanical ventilation duration was examined by multivariate analysis. The results demonstrated that two genetic polymorphisms, TNF-α-308G / A and L-1β-31C / T, were significantly correlated with ICU mortality in critically ill patients, especially those with sepsis. The results further suggest that the genotypes at these two polymorphic loci can be used in combination with the traditional clinical predictor APACHE II score to provide a more accurate prediction of patient outcomes.

  Applicants specifically incorporate the entire contents of all cited references in this disclosure. Further, where amounts, concentrations, or other values or parameters are shown as ranges, preferred ranges, or preferred upper limit values and preferred lower limit values lists, regardless of whether the ranges are disclosed separately. It should be understood that it specifically discloses the entire range consisting of any upper or preferred value and any pair of any lower or preferred value. Where numerical ranges are listed herein, unless otherwise specified, the ranges are intended to include their end points and all integers and fractions within the ranges. If a range is defined, the scope of the invention should not be limited to the specific values recited.

  Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The specification and examples are to be construed as merely illustrative.

Claims (5)

Genomic DNA is collected from a biological sample of a patient in clinical condition requiring intensive care, and inherited at position -308 of the TNF-α gene and position -31 of the IL-1β gene in the patient genomic DNA. Detection of genetic polymorphism using a sequencing system, and
Measure the patient's APACHE II score,
The presence of a G or A allele at position -308 of the TNF-α gene and a C or T allele at position -31 of the IL-1β gene ; and
When the APACHE II score is in the range of 55-71 ,
A method of assisting in predicting a clinical outcome of a patient in a clinical condition in need of intensive care comprising predicting that the patient's clinical outcome is death . 2. The method of claim 1 , wherein the patient in clinical condition requiring intensive care is a septic patient requiring intensive care . 3. The method of claim 1 or claim 2 , wherein the detection of the genetic polymorphism comprises amplifying a gene containing the polymorphism using an automated polymerase chain reaction (PCR) thermal sequencer. 3. A method according to claim 1 or claim 2 , wherein the sequencing system comprises electrophoresis. 3. A method according to claim 1 or claim 2 , wherein the sequencing system comprises an automatic sequencing system.

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